Palaeomagnetic field intensity variations suggest Mesoproterozoic inner-core nucleation

Abstract

The Earth’s inner core grows by the freezing of liquid iron at its surface. The point in history at which this process initiated marks a step-change in the thermal evolution of the planet. Recent computational and experimental studies1,2,3,4,5 have presented radically differing estimates of the thermal conductivity of the Earth’s core, resulting in estimates of the timing of inner-core nucleation ranging from less than half a billion to nearly two billion years ago. Recent inner-core nucleation (high thermal conductivity) requires high outer-core temperatures in the early Earth that complicate models of thermal evolution. The nucleation of the core leads to a different convective regime6 and potentially different magnetic field structures that produce an observable signal in the palaeomagnetic record and allow the date of inner-core nucleation to be estimated directly. Previous studies searching for this signature have been hampered by the paucity of palaeomagnetic intensity measurements, by the lack of an effective means of assessing their reliability, and by shorter-timescale geomagnetic variations. Here we examine results from an expanded Precambrian database of palaeomagnetic intensity measurements7 selected using a new set of reliability criteria8. Our analysis provides intensity-based support for the dominant dipolarity of the time-averaged Precambrian field, a crucial requirement for palaeomagnetic reconstructions of continents. We also present firm evidence for the existence of very long-term variations in geomagnetic strength. The most prominent and robust transition in the record is an increase in both average field strength and variability that is observed to occur between a billion and 1.5 billion years ago. This observation is most readily explained by the nucleation of the inner core occurring during this interval9; the timing would tend to favour a modest value of core thermal conductivity and supports a simple thermal evolution model for the Earth.

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Figure 1: Fits of palaeointensity data by minimum QPI value to palaeomagnetic inclination patterns predicted by a dipole field.
Figure 2: Four different representations of VDM versus age for all data with QPI ≥ 3.
Figure 3: Box-plot and summary statistics for different time intervals comprising VDM estimates with QPI ≥ 3.

References

  1. 1

    Pozzo, M., Davies, C., Gubbins, D. & Alfè, D. Thermal and electrical conductivity of iron at Earth’s core conditions. Nature 485, 355–358 (2012)

    ADS  CAS  Article  Google Scholar 

  2. 2

    Seagle, C. T., Cottrell, E., Fei, Y. W., Hummer, D. R. & Prakapenka, V. B. Electrical and thermal transport properties of iron and iron-silicon alloy at high pressure. Geophys. Res. Lett. 40, 5377–5381 (2013)

    ADS  CAS  Article  Google Scholar 

  3. 3

    Gomi, H. et al. The high conductivity of iron and thermal evolution of the Earth’s core. Phys. Earth Planet. Inter. 224, 88–103 (2013)

    ADS  CAS  Article  Google Scholar 

  4. 4

    de Koker, N., Steinle-Neumann, G. & Vlcek, V. Electrical resistivity and thermal conductivity of liquid Fe alloys at high P and T, and heat flux in Earth's core. Proc. Natl Acad. Sci. USA 109, 4070–4073 (2012)

    ADS  CAS  Article  Google Scholar 

  5. 5

    Zhang, P., Cohen, R. E. & Haule, K. Effects of electron correlations on transport properties of iron at Earth’s core conditions. Nature 517, 605–607 (2015)

    ADS  CAS  Article  Google Scholar 

  6. 6

    Aubert, J., Tarduno, J. A. & Johnson, C. L. Observations and models of the long-term evolution of Earth's magnetic field. Space Sci. Rev. 155, 337–370 (2010)

    ADS  CAS  Article  Google Scholar 

  7. 7

    Biggin, A. J., Strik, G. & Langereis, C. G. The intensity of the geomagnetic field in the late-Archaean: new measurements and an analysis of the updated IAGA palaeointensity database. Earth Planets Space 61, 9–22 (2009)

    ADS  Article  Google Scholar 

  8. 8

    Biggin, A. J. & Paterson, G. A. A new set of qualitative reliability criteria to aid inferences on palaeomagnetic dipole moment variations through geological time. Frontiers Earth Sci. 2, 21–29 (2014)

    ADS  Article  Google Scholar 

  9. 9

    Aubert, J., Labrosse, S. & Poitou, C. Modelling the palaeo-evolution of the geodynamo. Geophys. J. Int. 179, 1414–1428 (2009)

    ADS  Article  Google Scholar 

  10. 10

    Dunlop, D. J. & Yu, Y. in Timescales of the Internal Geomagnetic Field Vol. 145 of Geophysical Monograph Series (ed. Channell, J. E. T. ) 85–100 (AGU, 2004)

    Google Scholar 

  11. 11

    Prévot, M. & Perrin, M. Intensity of the Earth’s magnetic-field since precambrian from Thellier-type paleointensity data and inferences on the thermal history of the core. Geophys. J. Int. 108, 613–620 (1992)

    ADS  Article  Google Scholar 

  12. 12

    Biggin, A. J. & Thomas, D. N. Analysis of long-term variations in the geomagnetic poloidal field intensity and evaluation of their relationship with global geodynamics. Geophys. J. Int. 152, 392–415 (2003)

    ADS  Article  Google Scholar 

  13. 13

    Valet, J. P. Time variations in geomagnetic intensity. Rev. Geophys. 41, 1004, http://dx.doi.org/10.1029/2001RG000104 (2003)

    ADS  Article  Google Scholar 

  14. 14

    Biggin, A. J., Strik, G. H. M. A. & Langereis, C. G. Evidence for a very-long-term trend in geomagnetic secular variation. Nature Geosci. 1, 395–398 (2008)

    ADS  CAS  Article  Google Scholar 

  15. 15

    Macouin, M., Valet, J. P. & Besse, J. Long-term evolution of the geomagnetic dipole moment. Phys. Earth Planet. Inter. 147, 239–246 (2004)

    ADS  Article  Google Scholar 

  16. 16

    Tauxe, L. & Yamazaki, T. in Geomagnetism Vol. 5 of Treatise on Geophysics (ed. Kono, M. ) Ch. 13, 510–563 (Elsevier, 2007)

    Google Scholar 

  17. 17

    Valet, J. P., Besse, J., Kumar, A., Vadakke-Chanat, S. & Philippe, E. The intensity of the geomagnetic field from 2.4 Ga old Indian dykes. Geochem. Geophys. Geosyst. 15, 2426–2437 (2014)

    ADS  CAS  Article  Google Scholar 

  18. 18

    Evans, D. A. D. Proterozoic low orbital obliquity and axial-dipolar geomagnetic field from evaporite palaeolatitudes. Nature 444, 51–55 (2006)

    ADS  CAS  Article  Google Scholar 

  19. 19

    Veikkolainen, T., Evans, D. A. D., Korhonen, K. & Pesonen, L. J. On the low-inclination bias of the Precambrian geomagnetic field. Precambr. Res. 244, 23–32 (2014)

    ADS  CAS  Article  Google Scholar 

  20. 20

    Ziegler, L. B., Constable, C. G., Johnson, C. L. & Tauxe, L. PADM2M: a penalized maximum likelihood model of the 0–2 Ma palaeomagnetic axial dipole moment. Geophys. J. Int. 184, 1069–1089 (2011)

    ADS  Article  Google Scholar 

  21. 21

    Valet, J. P., Meynadier, L. & Guyodo, Y. Geomagnetic dipole strength and reversal rate over the past two million years. Nature 435, 802–805 (2005)

    ADS  CAS  Article  Google Scholar 

  22. 22

    Tauxe, L., Gee, J. S., Steiner, M. B. & Staudigel, H. Paleointensity results from the Jurassic: new constraints from submarine basaltic glasses of ODP Site 801C. Geochem. Geophys. Geosyst. 14, 4718–4733 (2013)

    ADS  CAS  Article  Google Scholar 

  23. 23

    de Groot, L. V., Fabian, K., Bakelaar, I. A. & Dekkers, M. J. Magnetic force microscopy reveals meta-stable magnetic domain states that prevent reliable absolute palaeointensity experiments. Nature Commun. 5, 4548, http://dx.doi.org/10.1038/Ncomms5548 (2014)

    ADS  CAS  Article  Google Scholar 

  24. 24

    Smirnov, A. V. & Tarduno, J. A. Thermochemical remanent magnetization in Precambrian rocks: are we sure the geomagnetic field was weak? J. Geophys. Res. 110, B06103 (2005)

    ADS  Article  Google Scholar 

  25. 25

    Tarduno, J. A. & Smirnov, A. V. in Timescales of the Paleomagnetic Field Vol. 145 Geophysical Monograph Series (eds Channell, J. E. T., Kent, D. V., Lowrie, W. & Meert, J. G. ) 328 (AGU, 2004)

    Google Scholar 

  26. 26

    Biggin, A. J. et al. Possible links between long-term geomagnetic variations and whole-mantle convection processes. Nature Geosci. 5, 526–533 (2012)

    ADS  CAS  Article  Google Scholar 

  27. 27

    Kulakov, E. V., Smirnov, A. V. & Diehl, J. F. Absolute geomagnetic paleointensity as recorded by similar to 1.09 Ga Lake Shore Traps (Keweenaw Peninsula, Michigan). Stud. Geophys. Geodaet. 57, 565–584 (2013)

    ADS  Article  Google Scholar 

  28. 28

    Thomas, N. An integrated rock magnetic approach to the selection or rejection of ancient basalt samples for paleointensity experiments. Phys. Earth Planet. Inter. 75, 329–342 (1993)

    ADS  Article  Google Scholar 

  29. 29

    Veikkolainen, T. & Pesonen, L. J. Palaeosecular variation, field reversals and the stability of the geodynamo in the Precambrian. Geophys. J. Int. 199, 1515–1526 (2014)

    ADS  Article  Google Scholar 

  30. 30

    Hunt, S. A. et al. On the increase in thermal diffusivity caused by the perovskite to post-perovskite phase transition and its implications for mantle dynamics. Earth Planet. Sci. Lett. 319–320, 96–103 (2012)

    ADS  Article  Google Scholar 

  31. 31

    Van der Voo, R. The reliability of paleomagnetic data. Tectonophysics 184, 1–9 (1990)

    ADS  Article  Google Scholar 

  32. 32

    Shaar, R. & Tauxe, L. Instability of thermoremanence and the problem of estimating the ancient geomagnetic field strength from non-single-domain recorders. Proc. Natl Acad. Sci. USA 112, 36, http://dx.doi.org/10.1073/pnas.1507986112 (2015)

    Article  Google Scholar 

Download references

Acknowledgements

We thank T. Torsvik for organising the 7th Nordic Supercontinents Meeting and acknowledge financial support for this from the European Research Council (ERC Advanced Grant 267631) and the Research Council of Norway through its Centres of Excellence funding scheme (CEED 223272). We also thank J. Rees and L. Waszek for discussions. A.J.B. acknowledges funding from a NERC standard grant (NE/H021043/1). G.A.P. acknowledges funding from an NSFC grant (41374072). L.T. acknowledges funding from an NSF grant (EAR 1345003).

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Authors

Contributions

A.J.B. designed the study. A.J.B., E.J.P., L.J.P. and T.V. assigned the QPI values. A.J.B., R.H., G.A.P., L.J.P., T.V. and L.T. wrote the paper. A.J.B., G.A.P. and T.V. analysed the data.

Corresponding author

Correspondence to A. J. Biggin.

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The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Four different representations of VDM versus time for all data with QPI ≥ 1.

a, Bubble plot, where size indicates QPI value. b, Density plot of number of measurements. c, Density plot of sum of QPI values. d, Box plot after binning with an interval length of 200 Myr (number of data in each are given with the number of published studies in parentheses). See Fig. 1 caption for an explanation of the box plot.

Extended Data Figure 2 Four different representations of VDM versus time for all data with QPI ≥ 2.

a, Bubble plot, where size indicates QPI value. b, Density plot of number of measurements. c, Density plot of sum of QPI values. d, Box plot after binning with an interval length of 200 Myr (number of data in each are given with the number of published studies in parentheses). See Fig. 1 caption for an explanation of the box plot.

Extended Data Figure 3 Four different representations of VDM versus time for all data with QPI ≥ 4.

a, Bubble plot, where size indicates QPI value. b, Density plot of number of measurements. c, Density plot of sum of QPI values. d, Box plot after binning with an interval length of 200 Myr (number of data in each are given with the number of published studies in parentheses). See Fig. 1 caption for an explanation of the box plot.

Extended Data Figure 4 Four different representations of VDM versus time for all data with QPI ≥ 5.

a, Bubble plot, where size indicates QPI value. b, Density plot of number of measurements. c, Density plot of sum of QPI values. d, Box plot after binning with an interval length of 200 Myr (number of data in each are given with the number of published studies in parentheses). See Fig. 1 legend for an explanation of the box plot.

Extended Data Figure 5 Box-plots for time intervals defined in the main text and summarized in Supplementary Table 3, comprising measurements with different minimum QPI values.

See Fig. 3 for QPI ≥ 3 plot and Fig. 1 caption for an explanation of the box plot. Thick error bars indicate 95% confidence limits (from 10,000 bootstraps) on the medians.

Extended Data Figure 6 Raw palaeointensity versus inclination data shown with a best-fitting dipole for the four studied time intervals.

Circle size indicates QPI value in panel a. In each case, the best-fitting dipole was found using the least-squares approach.

Extended Data Figure 7 Examples of two pseudo-data sets produced by one iteration of the new likelihood test.

See Methods for details. Each of the VADM estimates (red asterisks) are drawn from one of multiple 200-kyr-long sub-intervals (blue lines) of PADM2M20 (black line) which is rescaled by a random factor between 0.5 and 1.5. Data from the same mantle group are drawn from sub-intervals with the same rescaling to simulate the possible effects of mantle-forced variations. Data from the same secular variation groups are drawn from the same 200-kyr sub-interval to simulate the possible effects of further temporal clustering. Panel a shows an example using the mantle groups and secular variation groups of interval ‘Late’ and panel b shows the same for interval ‘Mid’.

Extended Data Table 1 Summary results from the Monte Carlo resampling test
Extended Data Table 2 Results of the tailored likelihood test applied to data sets in Supplementary Table 2

Supplementary information

Supplementary Table 1

Supplementary Table 1 shows the raw dataset used in this study. The format is identical to the PINT database (see http://earth.liv.ac.uk/pint/ for full details) with QPI criteria and values appended in the final column. (XLSX 240 kb)

Supplementary Table 2

Supplementary Table 2 contains a TAA summary of data with QPI values of at least 3 showing the Mantle Groups and Secular Variation (SV) Groups used in the new likelihood test (see Methods for details). For definition of Interval, refer to the main text. Ref No. refers to the Reference Number within the PINT database (http://earth.liv.ac.uk/pint/); NData refers to the number of site mean V(A)DM estimates; V(A)DMMed and V(A)DMIQR refer to the median and interquartile range of the V(A)DM estimates respectively. (XLSX 13 kb)

Supplementary Table 3

Supplementary Table 3 contains summary data for time intervals referred to in the main text and Figure 3 using minimum QPI values in the range 1-5. AgeMin and AgeMax refer to the minimum and maximum age estimates of the data within each interval. V(A)DMMed and V(A)DMIQR V(A)DMMed and V(A)DMIQR refer, respectively, to the median and interquartile range of the V(A)DM estimates within each interval and V(A)DM+95 and V(A)DM-95 refer to the 95% confidence limits on the median calculated using 10,000 bootstraps. NData refers to the number of V(A)DM estimates in each interval and NRef refers to the number of published studies that these are drawn from. In the final column, the P values produced by a series of Kolmogorv-Smirnov tests for equality of probability distribution are shown. The results are colour-coded according to the confidence with which the null hypothesis of identical distributions can be rejected as follows: red >99% confidence, orange >95% confidence, yellow > 90% confidence, green < 90% confidence. *Data in the RECENT interval were not assigned QPI values but rather selected on the basis of passing the criteria described in the Methods section. (XLSX 12 kb)

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Biggin, A., Piispa, E., Pesonen, L. et al. Palaeomagnetic field intensity variations suggest Mesoproterozoic inner-core nucleation. Nature 526, 245–248 (2015). https://doi.org/10.1038/nature15523

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